AMultivariate time-series corresponds to a temporally ordered set of variables. This mathematical representation has been used in countless domains such as finance, health, and biomechanics. Designing methods for automatically analyzing time-series (e.g. forecasting, classification, anomaly detection) has been widely investigated by researchers [1]}, [2]}. A particular focus is given to anomaly detection in time-series [3]}. In general, an anomaly or outlier can be defined as an observation or sample that does not follow an expected pattern. The popularity of anomaly detection in time-series is probably due to its interest in numerous industrial contexts. As an example, one can mention the detection of faulty sensors [4]}, fraudulent bank transactions [5]}, and pathologies in medical data [6]}.
